506 research outputs found

    A fast and flexible machine learning approach to data quality monitoring

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    We present a machine learning based approach for real-time monitoring of particle detectors. The proposed strategy evaluates the compatibility between incoming batches of experimental data and a reference sample representing the data behavior in normal conditions by implementing a likelihood-ratio hypothesis test. The core model is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. The resulting algorithm is fast, efficient and agnostic about the type of potential anomaly in the data. We show the performance of the model on multivariate data from a drift tube chambers muon detector

    Echinoderm larvae as bioindicators for the assessment of marine pollution: Sea urchin and sea cucumber responsiveness and future perspectives

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    Echinoderms play a crucial role in the functioning of marine ecosystems and due to their extensive distribution, rapid response, and the high sensitivity of their planktonic larvae to a large range of stressors, some species are widely used as biological indicators. In addition to sea urchins, sea cucumbers have recently been implemented in embryotoxicity bioassays showing high potential in ecotoxicological studies. However, the use of this species is still hindered by a lack of knowledge regarding their comparative responsiveness. The present study aimed to investigate the responsiveness of different echinoderm species to environmental pollution in order to develop their integration in batteries of ecotoxicological bioassays. To this end, the embryos of two sea urchins (Paracentrotus lividus and Arbacia lixula) and two sea cucumbers (Holothuria polii and Holothuria tubulosa) were incubated with inorganic and organic toxicants (cadmium, copper, mercury, lead, sodium dodecyl sulphate and 4-n-Nonhyphenol) and elutriates from contaminated marine sediments, chosen as a case study model. The results obtained, expressed through the percentage of abnormal embryos and Integrative Toxicity Indices (ITI), indicated species-specific sensitivities to pollutants, with comparable and correlated responsiveness between sea urchins and sea cucumbers. More specifically, sea cucumber larvae exposed to elutriates appear to be more sensitive than sea urchins, especially when incubated with samples containing trace metals, PCB and TBT. These results indicate that toxic responses in embryos exposed to environmental matrices are probably modulated by interactions between different variables, including additive, synergistic and antagonistic effects. These findings suggest that performing a larval test using different echinoderm classes can integrate the interactive effects of bioavailable fraction of contaminants on various levels, providing sensitive, representative and all year-round batteries of bioassays to apply in ecotoxicological studies

    Learning new physics efficiently with nonparametric methods

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    We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. Based on the original proposal by D'Agnolo and Wulzer (arXiv:1806.02350), the model evaluates the compatibility between experimental data and a reference model, by implementing a hypothesis testing procedure based on the likelihood ratio. Model-independence is enforced by avoiding any prior assumption about the presence or shape of new physics components in the measurements. We show that our approach has dramatic advantages compared to neural network implementations in terms of training times and computational resources, while maintaining comparable performances. In particular, we conduct our tests on higher dimensional datasets, a step forward with respect to previous studies.Comment: 22 pages, 13 figure

    Use of scalp cooling device to prevent alopecia for early breast cancer patients receiving chemotherapy: A prospective study

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    Chemotherapy-induced alopecia (CIA) affects the majority of patients receiving chemotherapy (CT) for early breast cancer. It is a highly distressing side effect of CT, with psychological and social impact. Primary aim of the present analysis was to assess the efficacy of scalp cooling with DigniCap¬ģ in preventing CIA. Success rate was defined as patients' self-reported hair loss <50% according to Dean scale. In this analysis, we reported success rate at 3 weeks after the first CT course and at 3 weeks after the last CT course. Secondary endpoints included self-reported tolerability and patients' judgment on scalp cooling performance. Consecutive early breast cancer patients admitted to Istituto Oncologico Veneto who were recommended to receive neoadjuvant or adjuvant CT, were eligible to undergo scalp cooling during the CT administration within this study. 135 patients were included: 74% received adjuvant CT and 26% neoadjuvant CT (P < .001). The type of CT was: docetaxel-cyclophosphamide (26%), paclitaxel (23%), epirubicin-cyclophosphamide followed by paclitaxel (32%), and paclitaxel followed by epirubicincyclophosphamide (19%). The rate of success in preventing alopecia was 77% (104/135) at 3 weeks from the start of CT and 60% (81/135) at 3 weeks from the end of treatment. Higher success rates were reported in non-anthracycline (71%) compared to anthracycline-containing CT regimens (54%; P < 0.001). Premature discontinuation of scalp cooling was reported in 29/135 patients (21.5%), including withdrawal for alopecia (16/29), for low scalp cooling tolerability (8/29) or both (5/29). Scalp cooling was generally well tolerated. These results overall suggest that the use of scalp cooling is effective in preventing alopecia in the majority of early breast cancer patients receiving neoadjuvant or adjuvant CT, especially for patients undergoing a taxane-based non-anthracycline regimen

    Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

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    Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR &lt; 60 mL/min/1.73 m2) or eGFR reduction &gt; 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR &lt; 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR &gt; 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

    Understanding Factors Associated With Psychomotor Subtypes of Delirium in Older Inpatients With Dementia

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    Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV